Data, Design and Deep Domain Knowledge: Science-Policy Collaboration to Combat Misinformation on Migration and Migrants

Marie McAuliffe, Guy Abel, Adrian Kitimbo, Jose Ignacio Martin Galan

    Research output: Contribution to journalArticlepeer-review

    Abstract

    In today’s data-rich societies there is a strong tendency to assess and analyze complex issues through quantitative methods utilizing new, and rapidly evolving and constantly expanding, user-generated data. While new data and new data science present enormous opportunities for innovation and scholarship, we are also witnessing intensification and expansion of digitalized public discourses that are increasingly enabling misinformation on migration and migrants through the devaluation of accurate data and evidence and proliferation of ‘fake news’ and inaccurate information. Harnessing ‘new’ data while utilizing ‘traditional’ migration data and offering new analytical perspectives underpinned by deep domain knowledge through collaborative science–policy partnerships extends knowledge, fosters inquiry, and promotes accurate understandings of migration. There is the critical role of global reference reports—such as the World Migration Report—that collate, present, and analyze data for consumption by general, policy, technical, and educational audiences. Maximizing utility of such reports requires investments in interactive data visualization that support sustainable efforts in countering misinformation on migration and migrants through engaging and appealing design that do not compromise accuracy, but act to promote it in an accessible way.
    Original languageEnglish
    JournalHarvard Data Science Review
    Volume4.1
    Issue numberWinter 2022
    DOIs
    Publication statusPublished - 2018

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